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Record W2758198288

Visitors or Stakeholders? The Role of International Students in Policy Development Related to the Internationalization of Higher Education

2017· article· en· W2758198288 on OpenAlexaffabout
Yuanyuan Zhang

Bibliographic record

Venue2017 Conference of the Canadian Society for the Study of Education · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Governance and Development
Canadian institutionsUniversity of Prince Edward Island
Fundersnot available
KeywordsInternationalizationHigher educationInstitutionInternational educationPolitical sciencePublic relationsInternationalization of Higher EducationSociologyPedagogyBusiness
DOInot available

Abstract

fetched live from OpenAlex

In this proposed research, I am going to examine the engagement of the voice of international students in internationalization policy making and implementation processes at on one post-secondary institution in the maritime area of east Canada. The purpose of the research is to reveal how and to what extent institutional administrators perceive and understand the growing appearance of international students on campus in terms of how and to what extent international students being included into internationalization policy making and implementing processes at one Canadian university. The findings of the research will be a reference for the university administrators when they make internationalization strategies that aim to bring balanced benefits to all stakeholders. It is also hoped that the discussion opened by this research on the possibility, approaches, and challenges of having international students involved in institutional strategy making processes goes beyond this specific university to a wider range of higher education institutions. Meanwhile, this research also sets the foundation for my further research on relations among three dimensions: internationalization strategies, internationalization models of institutes, and learning experiences of international students.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.389
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.061
GPT teacher head0.381
Teacher spread0.320 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2017
Admission routes2
Has abstractyes

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